Mobile/wireless devices are now commonplace among consumers and are used regularly to search for information, content and data on products and services across all industries. Retail and other enterprise environments can now use information gathered from mobile devices on their premises to engage visitors in more meaningful ways. Providing an entry point for mobile marketing, mobile devices are important to broadcast offers, information and location services to users who are on site or close thereto. However this information has low value if there is no additional information provided about what users are doing on the premise, where they are visiting, what their demographic information is, and pinpointing their needs and interest in a more targeted fashion. Providing an immersive environment where visitors, behavior can be predicted and influenced is a key objective to future retail, restaurant and other service industries.
Users and visitors to retail and other public environments (public zones) such as transit hubs, hospitals, schools and city streets may be immersed in zones where different types of radio based connectivity and communications points are available. WiFi, Bluetooth, Bluetooth Low Energy, 3G, 4G, LTE and others can provide venues for different means of communication with data and objects around the user. These technologies can provide different forms of information and access to internet data based on smartphone apps, browser based web applications, as well as analysis from visitor metrics collected from visitors to public zones to identify interests and needs. The providers of these technologies may be carriers, merchants, other enterprises, governmental agencies, security agencies and the like. These providers can use these technologies to allow local users (both actively or passively) to connect and receive specific information and services in the form of commercial offers, location based services and bandwidth/communications access. The technology providers can collect the user metrics (based on permissions, for example, from their profiles) including social WiFi login details, location and individual demographics for various commercial and customer assistance opportunities.
Wireless client devices connect to wireless access points or base-stations for communication. To ensure unique one-to-one communication, each device has a given unique identification address. For example, with the IEEE 802.11 wireless communication protocol, each device is given a unique media access control (MAC) address comprised of 6 hexadecimal octets. An example of a MAC address for a device is “00:FF:11:22:33:44:55.” A MAC address is a unique identifier typically assigned to network interfaces for communications on the physical network segment. MAC addresses are used as a network address for most IEEE 802 network technologies, including Ethernet and WiFi.
Each device employs a unique MAC address with this format when searching for a wireless base-station. Methods were devised to use this unique MAC address announcement for the purpose of identifying visitors for security purposes or when counting customers in a retail location. To prevent such observation, a mechanism of generating numerous extraneous randomized MAC addresses has been introduced by companies like Apple™ in IOS8™ as a method to provide better privacy to the devices.
This way, the MAC address changes when the mobile device is not connected to a network or access point and therefore the MAC address cannot be used to identify or track the device. Such randomization introduces unwanted phantom devices to obfuscate the real identified devices of value to the data gathering and analysis system. If such (raw or unfiltered) information is used, it will cause inaccuracy in new versus repeat visitor calculations and related analytics. For example, the randomized MAC address detected causes a measurement system to detect the device as a new device versus as a previously known (same) device. That is, if used as is, each random MAC address adds a false observation causing major inaccuracy in the observation/traffic data.
The MAC randomization has challenged tracking of individuals for security purposes as well as the measurement of unique MACs for traffic analysis since this prolific generation of random MAC addresses introduces unwanted phantom devices to obfuscate the real devices. If used “as is”, the information will cause difficulty in identifying real devices and cause inaccuracy in the typical new versus repeat visitor calculation. The random MAC addresses produced cause the measuring device to detect devices as new devices verses previously known devices, as this is the intent of the “privacy generating” randomization algorithm.
Traffic measurement of visitors to public environments (zones) is adversely affected by the MAC randomization because of the following:
a) Dwell-time anomalies, e.g., first and last seen                i) More observations with a dwell-time of <1 minute.        ii) More observations with a dwell-time <3 minute.        iii) More traffic w/a dwell-time between 3 and 20 minutes.        iv) Less traffic w/a dwell-time >20 minutes.        
b) New vs. Repeat inaccuracies                i) Dramatic increase of New so call “false” visitors.        ii) No or small decline in Repeat inaccuracies.        
In light of the above challenges caused by MAC privacy randomization, there is a need for a method and system that can undo or reverse MAC randomization for the purpose of tracking individuals and measuring visitor traffic.